Chapter 5 - Mobile Search Ranking

Abstract

The wide availability of Internet access on mobile devices, such as phones and personal media players, has allowed users to search and access Web information on the go. The availability of continuous fine-grained location information on these devices has enabled mobile local search, which employs user location as a key factor to search for local entities (e.g., a restaurant, store, gas station, or attraction), to overtake a significant part of the query volume. This is also evident by the rising popularity of location-based search engines on mobile devices, such as Bing Local, Google Local, Yahoo! Local, and Yelp. The quality of any mobile local search engine is mainly determined by its ranking function, which formally specifies how we retrieve and rank local entities in response to a user’s query. Acquiring effective ranking signals and heuristics to develop an effective ranking function is arguably the single most important research problem in mobile local search. This chapter first overviews the ranking signals in mobile local search (e.g., distance and customer rating score of a business), which have been recognized to be quite different from general Web search. We next present a recent data analysis that studies the behavior of mobile local search ranking signals using a large-scale query log, which reveals interesting heuristics that can be used to guide the exploitation of different signals to develop effective ranking features. Finally, we also discuss several interesting future research directions.